Open ghost opened 10 years ago
Hi,
I think that there is already a simple outlier supression that ignores voxels with very few observations. Frank is currently at ICRA but maybe he can point you to the corresponding line in the source code..
Cheers Jürgen
On Mon, Jun 2, 2014 at 8:45 PM, mojovski notifications@github.com wrote:
Hi Frank and others,
the "fastfusion" project is awesome! Thank you very much for sharing. How do you deal with outliers, e.g. sparse point measurements away from an object? I am looking for a solution to be used with stereo cameras, which are not as precise as the pattern systems aka. Kinect.
Is there a process reducing the "occupancy probability" of a node (=Brick, or Voxel) if no measurements are put into it after some time?
Thanks again!
— Reply to this email directly or view it on GitHub https://github.com/tum-vision/fastfusion/issues/1.
Hi Frank and others,
the "fastfusion" project is awesome! Thank you very much for sharing. How do you deal with outliers, e.g. sparse point measurements away from an object? I am looking for a solution to be used with stereo cameras, which are not as precise as the pattern systems aka. Kinect.
Is there a process reducing the "occupancy probability" of a node (=Brick, or Voxel) if no measurements are put into it after some time?
Thanks again!